Picture a farmer in 1916. He’s standing at the edge of a dirt road, arms crossed, watching his neighbour three concessions over unload a brand-new Fordson tractor from a flatbed. His horses are in the barn. His father’s plow is in the shed. His sons know how to handle both. And this noisy, unpredictable iron contraption? It might explode. It might get stuck in the mud. It might break down a hundred miles from the nearest mechanic.

He goes back to his horses.

Over the years that follow, his neighbour doubles his acreage. The farmer with the horses is selling off land to pay his mortgage.

I’ve been thinking about that story a lot lately. Because in 2026, every business owner I talk to is standing at the edge of the same dirt road — only this time, the machine on the flatbed is artificial intelligence.

The tractor took off faster than anyone expected

Here’s what actually happened. In 1916, about 20,000 tractors were sold in the United States. By 1935 — less than 20 years later — that number had jumped to more than one million. In the early 1920s, Henry Ford’s assembly line method finally made the tractor affordable for a small-acreage family farm — and Fordsons quickly became the leading tractor in North America.

And the farms that adopted early didn’t just work faster. They worked entirely differently. A tractor didn’t need six acres of hay to feed it through the winter, didn’t need shoeing, didn’t get sick. Those reclaimed acres went into cash crops. And because tractors could plow and harvest at more than double the speed of a horse team, planting and harvest windows shortened from weeks to days — which meant farmers could wait for peak ripeness instead of gambling against the weather. Economic historians estimate that by the mid-20th century, mechanization had saved American agriculture billions of man-hours per year in field work, hauling, and animal care combined.

And here’s the part nobody predicted in 1916: the whole country changed.

The second-order effects nobody saw coming

In 1900, roughly 60% of Americans lived in rural areas and close to 40% lived on farms. By 2000, only 20% lived in rural areas and just 2% on farms — even though the U.S. population had roughly tripled. The American farm population fell from 29 million to 5 million across the 20th century.

Smaller families followed. When you don’t need eight children to bring in the harvest, you stop having eight children. Kids who used to leave school at 13 or 14 for planting season started staying through high school and beyond. By 1920, every U.S. state required children aged 8 to 14 to attend school for at least part of the year — a standard that would have been unthinkable to a farm economy that needed every pair of hands in the field.

Those kids didn’t all go back to the farm. They went to cities, universities, and into industries that didn’t exist when their grandfathers first refused the Fordson. Mechanization didn’t eliminate work — it relocated it, upgraded it, and in the process, created the modern middle class.

None of that was visible from the edge of that dirt road in 1916.

Fast-forward to today

AI is to today’s business owners what the tractor was to the horse farmer of 1916. Some people fear it. Most have tried it. Many are overwhelmed — or have stopped short of using it for even basic tasks — because the learning curve feels too steep. And fearmongers keep warning that it’s coming for our jobs.

Which is partly true. Except.

Just as the tractor didn’t eliminate the horse or the need for agriculture, AI isn’t going to eliminate business or the people who run it. It will change how we work, how we make a living, and how we live — the same way mechanization changed all of it a century ago.

McKinsey’s 2025 global survey found that 88% of organizations now regularly use AI in at least one business function, up from 78% just a year earlier. Bain puts U.S. generative AI adoption at roughly 95% of companies. McKinsey estimates gen AI could deliver $2.6 to $4.4 trillion in annual value across marketing, customer operations, software, and R&D.

But here’s the number that should matter most to any business owner reading this: industries that have genuinely embraced AI are seeing labour productivity grow 4.8 times faster than the global average. That’s not a marginal edge. That’s the 1920s tractor gap all over again — showing up in quarterly numbers instead of crop yields.

And just like 1916, most adopters are still on the equivalent of hand-cranking. McKinsey found that only about a third of organizations have actually scaled their AI use across the enterprise. Around 6% are what they call “high performers” — the ones genuinely rewiring their workflows instead of bolting AI onto what they already do. Everybody else is experimenting.

And education is racing to catch up

This isn’t hypothetical for me. My son is graduating high school this year and applying to universities — and I find myself asking the question every parent should be asking right now: are universities actually prepared to teach in this new AI-driven world? Do they understand it themselves?

Because the old model — sit in rows, memorize, regurgitate — was built for the economy the tractor created. It isn’t built for the one AI is creating.

That’s why I got so genuinely excited after a recent conversation with Dr. Astrid Kuhn, founder of the Academy of Business Literacy & Entrepreneurship (ABLE) — a public charter junior and senior high school right here in Calgary for students who want something different.

ABLE’s whole model is built around one question: Is school preparing my teen for life after high school? Their answer is to teach what the next economy will actually reward — confidence with money, the ability to listen and work with people, and readiness for any path: trades, business, arts, medicine, or law. Every student launches a real project or venture each year. The Alberta curriculum gets delivered through hands-on application, not just textbooks. And because ABLE sits in the heart of Calgary’s entrepreneurial ecosystem, students walk into real environments — technology, arts, energy, banking — and learn from them directly.

This isn’t school separated from life. It’s school designed for it.

What ABLE is doing at the high-school level is exactly the kind of thinking universities and employers are going to need to embrace — fast. The kids graduating knowing how to talk to people, build something real, and adapt to tools that didn’t exist when they started grade nine are going to run circles around the ones still optimizing for standardized tests.

What this looks like on my desk

I’ll tell you what’s changed for me personally, because this is where theory meets a Thursday afternoon.

Earlier this week, a client asked me for a market brief, a proposal, and an initial strategy for an Alberta vertical they’re thinking of expanding into. In 2010, a team of specialists would have put many hours into that — working through repeated meetings, draft cycles, and sign-off loops just to lock down the strategic scaffold. Today, I framed it out in an afternoon.

All of it — the competitive map, the audience profile, the grant shortlist, the campaign workflow, the KPIs. Am I finished polishing it? Not yet. But I didn’t need a research specialist. I didn’t need a grant specialist. I didn’t need to spend hours digging through databases and industry reports myself — the grunt work that used to eat half any project timeline. I had a working draft ready for client review, and a framework strong enough to build the rest on.

Not by pressing a single magic button. By cross-pollinating. I’ll use one AI system for deep research and source triangulation, another for synthesis and structured writing, another for visualization or code, and a fourth to stress-test the logic. Some models are better at nuance; some are better at speed; some are better at following a strict structural brief. I treat them like I’d treat a team of human specialists — I assign tasks to strengths, I push back when something doesn’t feel right, I cross-check one against another, and I make the final call myself.

The result isn’t “AI-generated.” It’s AI-leveraged human expertise — 30 years of writing, marketing, research, and client relations applied at a speed and depth that would have been flatly impossible 15 years ago. What AI actually gives you is unmetered intelligence: expertise and analysis available any hour, on any question, without the clock running.

And this doesn’t happen by accident. I’ve built a working system. I create dedicated folders for each client where my AI tools absorb the history, the brand voice, the target audience, the campaigns that worked and the ones that didn’t — and through conversation after conversation, they also learn how I think and what I value. Every new project builds on every previous one. It compounds the way a long-time team member’s institutional knowledge compounds — except it’s instantly searchable, always available, and doesn’t take a competing job.

And the tools themselves keep evolving. While I was writing this very post, OpenAI rolled out workspace agents — scheduled AI agents that plug straight into business tools like Slack and run recurring tasks on their own. A layer of capability that didn’t exist 48 hours ago. By the time you’re reading this, there will be another.

The honest challenges

I’m not here to pretend this is friction-free. Some jobs will look different five years from now — the way a blacksmith’s job looked different by 1940. Some roles will disappear. Others will appear that we can’t even name yet. There are real questions about data privacy, about attribution, about creative authenticity, and about what happens to entry-level work when AI handles the first draft of everything.

The tractor raised those same questions. So did the personal computer. So did the internet. We worked through them — imperfectly, unevenly, but we worked through them — because the alternative was falling permanently behind.

The lesson from that dirt road

Right now, social media has us drowning in negative messaging about AI — the threats, the fears, the worst-case scenarios on a loop. I understand it. New technology always arrives with alarms attached. The tractor did. The automobile did. The internet did.

But step back for a second. Our grandparents and great-grandparents — yes, the ones with the horse and plow, squinting at that Fordson from across the field — would be overjoyed to live the life we live now. Indoor plumbing. Clean water. Medicine that adds decades to a lifespan. Work that doesn’t break a body by 50. A child’s future that doesn’t hinge on whether the harvest comes in.

We forget how far we’ve come. And we are obligated to educate the next generation for an optimistic, future-ready world — not a fearful, defensive one.

The farmers who thrived in the 20th century weren’t the ones who rushed recklessly into every new machine. They weren’t the ones who refused it, either. They were the ones who stayed curious, tested carefully, and refused to let fear disguise itself as wisdom. They asked how can this help me produce better work for the people I serve? — not how do I protect what I’ve always done?

That’s the question I’m asking every day right now — for my own business, for the advertisers I work with through Shine FM and IDMD Brand Management, and for the world my son and his classmates are about to step into. AI doesn’t replace strategy, relationship, or human judgment. It amplifies all three. And the businesses in Alberta that figure that out in 2026 will be the ones three concessions ahead of the field in 2030.

The Fordson is on the flatbed. The question isn’t whether it’ll change your industry.

The question is whether you’ll be the one driving it.

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Jodi Morel is the founder of IDMD Brand Management and the Alberta marketing representative for Shine FM. She helps local businesses pair brand-safe radio with AI-driven digital conversion funnels that deliver measurable results.